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and Health Data Science Mode of study: Full or Part-time study is possible Project Description: The successful candidate will work in a highly interdisciplinary environment as part of a vibrant cohort
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work on the relationship between AI and democratic ideals, an exploration of the history of algorithmic manipulation of democratic processes, examination of the role of the tech sector, including
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Deadline: 30 June 2025 A fully funded four-year PhD position is available to work on the project titled “Real-world quantum verification and benchmarking of noisy hardware”. This position is a
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
generate vast amounts of operational and maintenance data, much of it remains fragmented and underutilized. Unlocking insights from this unstructured data could enable earlier fault detection, improved
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Salary: Research Assistant: £32,546 to £34,132 per annum Research Associate: £35,116 to £37,174 per annum Newcastle University is a great place to work, with excellent benefits . We have a generous
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if this is the case. As this is the methodology used by government to assess and compare the energy and environmental performance of dwellings, the current rating disincentivises developers from specifying
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. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and accretion. Previous work
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experiments; supporting other group members with data analysis and interpretation from both simulations and experimental data; and use the developed framework to design new materials with optimised performance
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sustainable operations in diverse industrial environments. Number Of Awards: 1 Start Date: 1st October 2025 Award Duration: 4 years Application Closing Date: 16th June 2025 Sponsor EPSRC Supervisors Dr Zepeng
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become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address